no code implementations • 30 Oct 2022 • Dong-Ho Lee, Akshen Kadakia, Brihi Joshi, Aaron Chan, Ziyi Liu, Kiran Narahari, Takashi Shibuya, Ryosuke Mitani, Toshiyuki Sekiya, Jay Pujara, Xiang Ren
Explanation-based model debugging aims to resolve spurious biases by showing human users explanations of model behavior, asking users to give feedback on the behavior, then using the feedback to update the model.
no code implementations • 24 Jan 2022 • Rem Hida, Masaki Hamada, Chie Kamada, Emiru Tsunoo, Toshiyuki Sekiya, Toshiyuki Kumakura
Although end-to-end text-to-speech (TTS) models can generate natural speech, challenges still remain when it comes to estimating sentence-level phonetic and prosodic information from raw text in Japanese TTS systems.
1 code implementation • ACL 2022 • Dong-Ho Lee, Akshen Kadakia, Kangmin Tan, Mahak Agarwal, Xinyu Feng, Takashi Shibuya, Ryosuke Mitani, Toshiyuki Sekiya, Jay Pujara, Xiang Ren
We also find that good demonstration can save many labeled examples and consistency in demonstration contributes to better performance.
no code implementations • SEMEVAL 2019 • Masahiro Yamamoto, Toshiyuki Sekiya
In Subtask B, the cross domain suggestion mining task, we apply the idea of distant supervision.